Changes
On April 29, 2024 at 9:43:12 AM UTC, kennedysenagi:
-
No fields were updated. See the metadata diff for more details.
f | 1 | { | f | 1 | { |
2 | "acknowledgement": "The authors gratefully acknowledge the financial | 2 | "acknowledgement": "The authors gratefully acknowledge the financial | ||
3 | support for this research by the following organizations and agencies: | 3 | support for this research by the following organizations and agencies: | ||
4 | Kenya Education Network Trust (KENET) - Grant Number AGMT1170; | 4 | Kenya Education Network Trust (KENET) - Grant Number AGMT1170; | ||
5 | Foreign, Commonwealth & Development Office (FCDO) [IMC-Grant 21108]; | 5 | Foreign, Commonwealth & Development Office (FCDO) [IMC-Grant 21108]; | ||
6 | Australian Centre for International Agricultural Research (ACIAR) | 6 | Australian Centre for International Agricultural Research (ACIAR) | ||
7 | (ProteinAfrica \u2013 Grant No: LS/2020/154), the Rockefeller | 7 | (ProteinAfrica \u2013 Grant No: LS/2020/154), the Rockefeller | ||
8 | Foundation (WAVE-IN\u2014 Grant No: 2021 FOD 030); Bill & Melinda | 8 | Foundation (WAVE-IN\u2014 Grant No: 2021 FOD 030); Bill & Melinda | ||
9 | Gates Foundation (INV-032416); IKEA Foundation (G-2204-02144), Horizon | 9 | Gates Foundation (INV-032416); IKEA Foundation (G-2204-02144), Horizon | ||
10 | Europe (NESTLER - Project: 101060762 - HORIZON-CL6-2021- | 10 | Europe (NESTLER - Project: 101060762 - HORIZON-CL6-2021- | ||
11 | FARM2FORK-01), the Curt Bergfors Foundation Food Planet Prize Award; | 11 | FARM2FORK-01), the Curt Bergfors Foundation Food Planet Prize Award; | ||
12 | Norwegian Agency for Development Cooperation, the Section for | 12 | Norwegian Agency for Development Cooperation, the Section for | ||
13 | Research, Innovation and Higher Education grant number RAF\u20133058 | 13 | Research, Innovation and Higher Education grant number RAF\u20133058 | ||
14 | KEN\u201318/0005 (CAP\u2013Africa); the Swedish International | 14 | KEN\u201318/0005 (CAP\u2013Africa); the Swedish International | ||
15 | Development Cooperation Agency (SIDA); the Swiss Agency for | 15 | Development Cooperation Agency (SIDA); the Swiss Agency for | ||
16 | Development and Cooperation (SDC); the Australian Centre for | 16 | Development and Cooperation (SDC); the Australian Centre for | ||
17 | International Agricultural Research (ACIAR); the Norwegian Agency for | 17 | International Agricultural Research (ACIAR); the Norwegian Agency for | ||
18 | Development Cooperation (NORAD); the German Federal Ministry for | 18 | Development Cooperation (NORAD); the German Federal Ministry for | ||
19 | Economic Cooperation and Development (BMZ); the Federal Democratic | 19 | Economic Cooperation and Development (BMZ); the Federal Democratic | ||
20 | Republic of Ethiopia; and the Government of the Republic of Kenya. The | 20 | Republic of Ethiopia; and the Government of the Republic of Kenya. The | ||
21 | funders had no role in study design, data collection and analysis, | 21 | funders had no role in study design, data collection and analysis, | ||
22 | decision to publish, or preparation of the manuscript. ", | 22 | decision to publish, or preparation of the manuscript. ", | ||
23 | "administrative_areas": "Nairobi", | 23 | "administrative_areas": "Nairobi", | ||
24 | "author": null, | 24 | "author": null, | ||
25 | "author_email": null, | 25 | "author_email": null, | ||
26 | "citation_narrative": "DOI: 10.3389/frai.2024.1403593", | 26 | "citation_narrative": "DOI: 10.3389/frai.2024.1403593", | ||
27 | "collaborators": "[{\"collaborator\": \"Henry Kyalo\"}, | 27 | "collaborators": "[{\"collaborator\": \"Henry Kyalo\"}, | ||
28 | {\"collaborator\": \"Henri E. Z. Tonnang\"}, {\"collaborator\": | 28 | {\"collaborator\": \"Henri E. Z. Tonnang\"}, {\"collaborator\": | ||
29 | \"James Egonyu\"}, {\"collaborator\": \"John Olukuru\"}, | 29 | \"James Egonyu\"}, {\"collaborator\": \"John Olukuru\"}, | ||
30 | {\"collaborator\": \"Chrysantus M. Tanga\"}]", | 30 | {\"collaborator\": \"Chrysantus M. Tanga\"}]", | ||
31 | "contact_person": "Kennedy Senagi", | 31 | "contact_person": "Kennedy Senagi", | ||
32 | "contact_person_email": "ksenagi@icipe.org", | 32 | "contact_person_email": "ksenagi@icipe.org", | ||
33 | "country": "[{\"country\": \"KE\"}]", | 33 | "country": "[{\"country\": \"KE\"}]", | ||
34 | "creator_user_id": "f09ec764-fe3c-4069-850b-f968ff0c20bb", | 34 | "creator_user_id": "f09ec764-fe3c-4069-850b-f968ff0c20bb", | ||
35 | "date_uploaded": "2024-04-26", | 35 | "date_uploaded": "2024-04-26", | ||
36 | "donor": "Kenya Education Network Trust (KENET)", | 36 | "donor": "Kenya Education Network Trust (KENET)", | ||
37 | "end_date": "2024-04-26", | 37 | "end_date": "2024-04-26", | ||
38 | "groups": [], | 38 | "groups": [], | ||
39 | "id": "59311393-3b0b-4f79-92b3-62a9b30a89ff", | 39 | "id": "59311393-3b0b-4f79-92b3-62a9b30a89ff", | ||
40 | "isopen": false, | 40 | "isopen": false, | ||
41 | "license_id": "cc-nc", | 41 | "license_id": "cc-nc", | ||
42 | "license_title": "Creative Commons Non-Commercial (Any)", | 42 | "license_title": "Creative Commons Non-Commercial (Any)", | ||
43 | "license_url": "http://creativecommons.org/licenses/by-nc/2.0/", | 43 | "license_url": "http://creativecommons.org/licenses/by-nc/2.0/", | ||
44 | "maintainer": "Kennedy Senagi", | 44 | "maintainer": "Kennedy Senagi", | ||
45 | "maintainer_email": "ksenagi@icipe.org", | 45 | "maintainer_email": "ksenagi@icipe.org", | ||
46 | "metadata_created": "2024-04-29T09:38:54.556778", | 46 | "metadata_created": "2024-04-29T09:38:54.556778", | ||
n | 47 | "metadata_modified": "2024-04-29T09:43:07.073338", | n | 47 | "metadata_modified": "2024-04-29T09:43:12.430656", |
48 | "name": | 48 | "name": | ||
49 | p-learning-algorithms-in-farming-edible-crickets-as-a-source-of-food", | 49 | p-learning-algorithms-in-farming-edible-crickets-as-a-source-of-food", | ||
50 | "notes": "Crickets (Gryllus bimaculatus) produce sounds as a natural | 50 | "notes": "Crickets (Gryllus bimaculatus) produce sounds as a natural | ||
51 | means to communicate and convey various behaviors and activities, | 51 | means to communicate and convey various behaviors and activities, | ||
52 | including mating, feeding, aggression, distress, and more. These | 52 | including mating, feeding, aggression, distress, and more. These | ||
53 | vocalizations are intricately linked to prevailing environmental | 53 | vocalizations are intricately linked to prevailing environmental | ||
54 | conditions such as temperature and humidity. By accurately monitoring, | 54 | conditions such as temperature and humidity. By accurately monitoring, | ||
55 | identifying, and appropriately addressing these behaviors and | 55 | identifying, and appropriately addressing these behaviors and | ||
56 | activities, the farming and production of crickets can be enhanced. | 56 | activities, the farming and production of crickets can be enhanced. | ||
57 | This research implemented a decision support system that leverages | 57 | This research implemented a decision support system that leverages | ||
58 | machine learning (ML) algorithms to decode and classify cricket songs, | 58 | machine learning (ML) algorithms to decode and classify cricket songs, | ||
59 | along with their associated key weather variables (temperature and | 59 | along with their associated key weather variables (temperature and | ||
60 | humidity). Videos capturing cricket behavior and weather variables | 60 | humidity). Videos capturing cricket behavior and weather variables | ||
61 | were recorded. From these videos, sound signals were extracted and | 61 | were recorded. From these videos, sound signals were extracted and | ||
62 | classified such as calling, aggression, and courtship. Numerical and | 62 | classified such as calling, aggression, and courtship. Numerical and | ||
63 | image features were extracted from the sound signals and combined with | 63 | image features were extracted from the sound signals and combined with | ||
64 | the weather variables. The extracted numerical features, i.e., | 64 | the weather variables. The extracted numerical features, i.e., | ||
65 | Mel-Frequency Cepstral Coefficients (MFCC), Linear Frequency Cepstral | 65 | Mel-Frequency Cepstral Coefficients (MFCC), Linear Frequency Cepstral | ||
66 | Coefficients, and chroma, were used to train shallow (support vector | 66 | Coefficients, and chroma, were used to train shallow (support vector | ||
67 | machine, k-nearest neighbors, and random forest (RF)) ML algorithms. | 67 | machine, k-nearest neighbors, and random forest (RF)) ML algorithms. | ||
68 | While image features, i.e., spectrograms, were used to train different | 68 | While image features, i.e., spectrograms, were used to train different | ||
69 | state-of-the-art deep ML models, i,e., convolutional neural network} | 69 | state-of-the-art deep ML models, i,e., convolutional neural network} | ||
70 | architectures (ResNet152V2, VGG16, and EfficientNetB4). In the deep ML | 70 | architectures (ResNet152V2, VGG16, and EfficientNetB4). In the deep ML | ||
71 | category, ResNet152V2 had the best accuracy of 99.42%. The RF | 71 | category, ResNet152V2 had the best accuracy of 99.42%. The RF | ||
72 | algorithm had the best accuracy of 95.63% in the shallow ML category | 72 | algorithm had the best accuracy of 95.63% in the shallow ML category | ||
73 | when trained with a combination of MFCC+chroma and after feature | 73 | when trained with a combination of MFCC+chroma and after feature | ||
74 | selection. In descending order of importance, the top 6 ranked | 74 | selection. In descending order of importance, the top 6 ranked | ||
75 | features in the RF algorithm were, namely humidity, temperature, C#, | 75 | features in the RF algorithm were, namely humidity, temperature, C#, | ||
76 | mfcc11, mfcc10, and D. From the selected features. With this | 76 | mfcc11, mfcc10, and D. From the selected features. With this | ||
77 | information, it is notable that insects require specific temperatures | 77 | information, it is notable that insects require specific temperatures | ||
78 | and humidity for growth and metabolic activities. Moreover, the songs | 78 | and humidity for growth and metabolic activities. Moreover, the songs | ||
79 | produced by certain cricket species naturally align to musical tones | 79 | produced by certain cricket species naturally align to musical tones | ||
80 | such as C# and D as ranked by the algorithm. Using this knowledge, a | 80 | such as C# and D as ranked by the algorithm. Using this knowledge, a | ||
81 | decision support system was built to guide farmers about the optimal | 81 | decision support system was built to guide farmers about the optimal | ||
82 | temperature and humidity ranges and interpret the songs (calling, | 82 | temperature and humidity ranges and interpret the songs (calling, | ||
83 | aggression, and courtship) in relation to weather variables. With this | 83 | aggression, and courtship) in relation to weather variables. With this | ||
84 | information, farmers can put in place suitable measures such as | 84 | information, farmers can put in place suitable measures such as | ||
85 | temperature regulation, humidity control, addressing aggressors, and | 85 | temperature regulation, humidity control, addressing aggressors, and | ||
86 | other relevant interventions to minimize or eliminate losses and | 86 | other relevant interventions to minimize or eliminate losses and | ||
87 | enhance cricket production.", | 87 | enhance cricket production.", | ||
88 | "num_resources": 4, | 88 | "num_resources": 4, | ||
89 | "num_tags": 6, | 89 | "num_tags": 6, | ||
90 | "organization": { | 90 | "organization": { | ||
91 | "approval_status": "approved", | 91 | "approval_status": "approved", | ||
92 | "created": "2022-05-17T13:53:24.098004", | 92 | "created": "2022-05-17T13:53:24.098004", | ||
93 | "description": "", | 93 | "description": "", | ||
94 | "id": "d16ea320-c49c-4a2e-b419-49c90c384c7d", | 94 | "id": "d16ea320-c49c-4a2e-b419-49c90c384c7d", | ||
95 | "image_url": "2022-05-17-135324.083479bees.jpeg", | 95 | "image_url": "2022-05-17-135324.083479bees.jpeg", | ||
96 | "is_organization": true, | 96 | "is_organization": true, | ||
97 | "name": "environmental-health", | 97 | "name": "environmental-health", | ||
98 | "state": "active", | 98 | "state": "active", | ||
99 | "title": "Environmental Health", | 99 | "title": "Environmental Health", | ||
100 | "type": "organization" | 100 | "type": "organization" | ||
101 | }, | 101 | }, | ||
102 | "owner_org": "d16ea320-c49c-4a2e-b419-49c90c384c7d", | 102 | "owner_org": "d16ea320-c49c-4a2e-b419-49c90c384c7d", | ||
103 | "principal_investigator": "Kennedy Senagi", | 103 | "principal_investigator": "Kennedy Senagi", | ||
104 | "principal_investigator_email": "ksenagi@icipe.org", | 104 | "principal_investigator_email": "ksenagi@icipe.org", | ||
105 | "private": false, | 105 | "private": false, | ||
106 | "region": "Nairobi", | 106 | "region": "Nairobi", | ||
107 | "relationships_as_object": [], | 107 | "relationships_as_object": [], | ||
108 | "relationships_as_subject": [], | 108 | "relationships_as_subject": [], | ||
109 | "resources": [ | 109 | "resources": [ | ||
110 | { | 110 | { | ||
111 | "cache_last_updated": null, | 111 | "cache_last_updated": null, | ||
112 | "cache_url": null, | 112 | "cache_url": null, | ||
113 | "created": "2024-04-29T09:40:16.621911", | 113 | "created": "2024-04-29T09:40:16.621911", | ||
114 | "date_last_updated": "2024-04-26", | 114 | "date_last_updated": "2024-04-26", | ||
115 | "date_uploaded_resource": "2024-04-26", | 115 | "date_uploaded_resource": "2024-04-26", | ||
116 | "description": "", | 116 | "description": "", | ||
117 | "format": "CSV", | 117 | "format": "CSV", | ||
118 | "hash": "", | 118 | "hash": "", | ||
119 | "id": "91644e4e-7951-4ed4-8533-c52c7451e557", | 119 | "id": "91644e4e-7951-4ed4-8533-c52c7451e557", | ||
120 | "last_modified": "2024-04-29T09:40:16.569668", | 120 | "last_modified": "2024-04-29T09:40:16.569668", | ||
121 | "metadata_modified": "2024-04-29T09:40:16.591494", | 121 | "metadata_modified": "2024-04-29T09:40:16.591494", | ||
122 | "mimetype": "text/csv", | 122 | "mimetype": "text/csv", | ||
123 | "mimetype_inner": null, | 123 | "mimetype_inner": null, | ||
124 | "name": "Main metadata sheet", | 124 | "name": "Main metadata sheet", | ||
125 | "package_id": "59311393-3b0b-4f79-92b3-62a9b30a89ff", | 125 | "package_id": "59311393-3b0b-4f79-92b3-62a9b30a89ff", | ||
126 | "position": 0, | 126 | "position": 0, | ||
127 | "resource_type": null, | 127 | "resource_type": null, | ||
128 | "restricted": "{\"allowed_users\": \"\", \"level\": | 128 | "restricted": "{\"allowed_users\": \"\", \"level\": | ||
129 | \"public\"}", | 129 | \"public\"}", | ||
130 | "size": 58048, | 130 | "size": 58048, | ||
131 | "state": "active", | 131 | "state": "active", | ||
132 | "url": | 132 | "url": | ||
133 | 1644e4e-7951-4ed4-8533-c52c7451e557/download/main-metadata-sheet.csv", | 133 | 1644e4e-7951-4ed4-8533-c52c7451e557/download/main-metadata-sheet.csv", | ||
134 | "url_type": "upload" | 134 | "url_type": "upload" | ||
135 | }, | 135 | }, | ||
136 | { | 136 | { | ||
137 | "cache_last_updated": null, | 137 | "cache_last_updated": null, | ||
138 | "cache_url": null, | 138 | "cache_url": null, | ||
139 | "created": "2024-04-29T09:41:11.304003", | 139 | "created": "2024-04-29T09:41:11.304003", | ||
140 | "date_last_updated": "2024-04-26", | 140 | "date_last_updated": "2024-04-26", | ||
141 | "date_uploaded_resource": "2024-04-26", | 141 | "date_uploaded_resource": "2024-04-26", | ||
142 | "description": "", | 142 | "description": "", | ||
143 | "format": "CSV", | 143 | "format": "CSV", | ||
144 | "hash": "", | 144 | "hash": "", | ||
145 | "id": "a6ea37de-2203-400f-8bd1-49e3a7d84923", | 145 | "id": "a6ea37de-2203-400f-8bd1-49e3a7d84923", | ||
146 | "last_modified": "2024-04-29T09:41:11.256196", | 146 | "last_modified": "2024-04-29T09:41:11.256196", | ||
147 | "metadata_modified": "2024-04-29T09:41:11.276536", | 147 | "metadata_modified": "2024-04-29T09:41:11.276536", | ||
148 | "mimetype": "text/csv", | 148 | "mimetype": "text/csv", | ||
149 | "mimetype_inner": null, | 149 | "mimetype_inner": null, | ||
150 | "name": "Chroma + weather features, and lables", | 150 | "name": "Chroma + weather features, and lables", | ||
151 | "package_id": "59311393-3b0b-4f79-92b3-62a9b30a89ff", | 151 | "package_id": "59311393-3b0b-4f79-92b3-62a9b30a89ff", | ||
152 | "position": 1, | 152 | "position": 1, | ||
153 | "resource_type": null, | 153 | "resource_type": null, | ||
154 | "restricted": "{\"allowed_users\": \"\", \"level\": | 154 | "restricted": "{\"allowed_users\": \"\", \"level\": | ||
155 | \"public\"}", | 155 | \"public\"}", | ||
156 | "size": 2244601, | 156 | "size": 2244601, | ||
157 | "state": "active", | 157 | "state": "active", | ||
158 | "url": | 158 | "url": | ||
159 | 0f-8bd1-49e3a7d84923/download/chroma-weather-features-and-lables.csv", | 159 | 0f-8bd1-49e3a7d84923/download/chroma-weather-features-and-lables.csv", | ||
160 | "url_type": "upload" | 160 | "url_type": "upload" | ||
161 | }, | 161 | }, | ||
162 | { | 162 | { | ||
163 | "cache_last_updated": null, | 163 | "cache_last_updated": null, | ||
164 | "cache_url": null, | 164 | "cache_url": null, | ||
165 | "created": "2024-04-29T09:42:08.763024", | 165 | "created": "2024-04-29T09:42:08.763024", | ||
166 | "date_last_updated": "2024-04-26", | 166 | "date_last_updated": "2024-04-26", | ||
167 | "date_uploaded_resource": "2024-04-26", | 167 | "date_uploaded_resource": "2024-04-26", | ||
168 | "description": "", | 168 | "description": "", | ||
169 | "format": "CSV", | 169 | "format": "CSV", | ||
170 | "hash": "", | 170 | "hash": "", | ||
171 | "id": "81a9f5ba-c7e4-4ece-ac39-8a4f2c10089b", | 171 | "id": "81a9f5ba-c7e4-4ece-ac39-8a4f2c10089b", | ||
172 | "last_modified": "2024-04-29T09:42:08.712541", | 172 | "last_modified": "2024-04-29T09:42:08.712541", | ||
173 | "metadata_modified": "2024-04-29T09:42:08.736301", | 173 | "metadata_modified": "2024-04-29T09:42:08.736301", | ||
174 | "mimetype": "text/csv", | 174 | "mimetype": "text/csv", | ||
175 | "mimetype_inner": null, | 175 | "mimetype_inner": null, | ||
176 | "name": "MFCC + weather features, and lables", | 176 | "name": "MFCC + weather features, and lables", | ||
177 | "package_id": "59311393-3b0b-4f79-92b3-62a9b30a89ff", | 177 | "package_id": "59311393-3b0b-4f79-92b3-62a9b30a89ff", | ||
178 | "position": 2, | 178 | "position": 2, | ||
179 | "resource_type": null, | 179 | "resource_type": null, | ||
180 | "restricted": "{\"allowed_users\": \"\", \"level\": | 180 | "restricted": "{\"allowed_users\": \"\", \"level\": | ||
181 | \"public\"}", | 181 | \"public\"}", | ||
182 | "size": 1748935, | 182 | "size": 1748935, | ||
183 | "state": "active", | 183 | "state": "active", | ||
184 | "url": | 184 | "url": | ||
185 | 4ece-ac39-8a4f2c10089b/download/mfcc-weather-features-and-lables.csv", | 185 | 4ece-ac39-8a4f2c10089b/download/mfcc-weather-features-and-lables.csv", | ||
186 | "url_type": "upload" | 186 | "url_type": "upload" | ||
187 | }, | 187 | }, | ||
188 | { | 188 | { | ||
189 | "cache_last_updated": null, | 189 | "cache_last_updated": null, | ||
190 | "cache_url": null, | 190 | "cache_url": null, | ||
191 | "created": "2024-04-29T09:43:07.106575", | 191 | "created": "2024-04-29T09:43:07.106575", | ||
192 | "date_last_updated": "2024-04-26", | 192 | "date_last_updated": "2024-04-26", | ||
193 | "date_uploaded_resource": "2024-04-26", | 193 | "date_uploaded_resource": "2024-04-26", | ||
194 | "description": "", | 194 | "description": "", | ||
195 | "format": "CSV", | 195 | "format": "CSV", | ||
196 | "hash": "", | 196 | "hash": "", | ||
197 | "id": "5fc15f5e-a24a-409f-b088-586e22b337ca", | 197 | "id": "5fc15f5e-a24a-409f-b088-586e22b337ca", | ||
198 | "last_modified": "2024-04-29T09:43:07.052737", | 198 | "last_modified": "2024-04-29T09:43:07.052737", | ||
199 | "metadata_modified": "2024-04-29T09:43:07.079612", | 199 | "metadata_modified": "2024-04-29T09:43:07.079612", | ||
200 | "mimetype": "text/csv", | 200 | "mimetype": "text/csv", | ||
201 | "mimetype_inner": null, | 201 | "mimetype_inner": null, | ||
202 | "name": "LFCC + weather features, and lables", | 202 | "name": "LFCC + weather features, and lables", | ||
203 | "package_id": "59311393-3b0b-4f79-92b3-62a9b30a89ff", | 203 | "package_id": "59311393-3b0b-4f79-92b3-62a9b30a89ff", | ||
204 | "position": 3, | 204 | "position": 3, | ||
205 | "resource_type": null, | 205 | "resource_type": null, | ||
206 | "restricted": "{\"allowed_users\": \"\", \"level\": | 206 | "restricted": "{\"allowed_users\": \"\", \"level\": | ||
207 | \"public\"}", | 207 | \"public\"}", | ||
208 | "size": 24101790, | 208 | "size": 24101790, | ||
209 | "state": "active", | 209 | "state": "active", | ||
210 | "url": | 210 | "url": | ||
211 | 409f-b088-586e22b337ca/download/lfcc-weather-features-and-lables.csv", | 211 | 409f-b088-586e22b337ca/download/lfcc-weather-features-and-lables.csv", | ||
212 | "url_type": "upload" | 212 | "url_type": "upload" | ||
213 | } | 213 | } | ||
214 | ], | 214 | ], | ||
215 | "start_date": "2024-04-26", | 215 | "start_date": "2024-04-26", | ||
t | 216 | "state": "draft", | t | 216 | "state": "active", |
217 | "tags": [ | 217 | "tags": [ | ||
218 | { | 218 | { | ||
219 | "display_name": "Insects", | 219 | "display_name": "Insects", | ||
220 | "id": "9c6eae2d-7311-41e5-958f-3b11a4a905d8", | 220 | "id": "9c6eae2d-7311-41e5-958f-3b11a4a905d8", | ||
221 | "name": "Insects", | 221 | "name": "Insects", | ||
222 | "state": "active", | 222 | "state": "active", | ||
223 | "vocabulary_id": null | 223 | "vocabulary_id": null | ||
224 | }, | 224 | }, | ||
225 | { | 225 | { | ||
226 | "display_name": "decision support system", | 226 | "display_name": "decision support system", | ||
227 | "id": "22b7773d-18d8-4b5d-a86d-7058197312a0", | 227 | "id": "22b7773d-18d8-4b5d-a86d-7058197312a0", | ||
228 | "name": "decision support system", | 228 | "name": "decision support system", | ||
229 | "state": "active", | 229 | "state": "active", | ||
230 | "vocabulary_id": null | 230 | "vocabulary_id": null | ||
231 | }, | 231 | }, | ||
232 | { | 232 | { | ||
233 | "display_name": "deep learning", | 233 | "display_name": "deep learning", | ||
234 | "id": "0265fb58-9cd3-4d0d-8215-2f0b571a09f4", | 234 | "id": "0265fb58-9cd3-4d0d-8215-2f0b571a09f4", | ||
235 | "name": "deep learning", | 235 | "name": "deep learning", | ||
236 | "state": "active", | 236 | "state": "active", | ||
237 | "vocabulary_id": null | 237 | "vocabulary_id": null | ||
238 | }, | 238 | }, | ||
239 | { | 239 | { | ||
240 | "display_name": "machine learning", | 240 | "display_name": "machine learning", | ||
241 | "id": "3638359c-f3cb-452c-ac1a-57193f56c880", | 241 | "id": "3638359c-f3cb-452c-ac1a-57193f56c880", | ||
242 | "name": "machine learning", | 242 | "name": "machine learning", | ||
243 | "state": "active", | 243 | "state": "active", | ||
244 | "vocabulary_id": null | 244 | "vocabulary_id": null | ||
245 | }, | 245 | }, | ||
246 | { | 246 | { | ||
247 | "display_name": "sound classification", | 247 | "display_name": "sound classification", | ||
248 | "id": "e5acbf75-416c-4213-abc9-bfd0a0cca7d9", | 248 | "id": "e5acbf75-416c-4213-abc9-bfd0a0cca7d9", | ||
249 | "name": "sound classification", | 249 | "name": "sound classification", | ||
250 | "state": "active", | 250 | "state": "active", | ||
251 | "vocabulary_id": null | 251 | "vocabulary_id": null | ||
252 | }, | 252 | }, | ||
253 | { | 253 | { | ||
254 | "display_name": "transfer learning", | 254 | "display_name": "transfer learning", | ||
255 | "id": "837a5abb-e47d-4c1e-88e1-5c75879de94d", | 255 | "id": "837a5abb-e47d-4c1e-88e1-5c75879de94d", | ||
256 | "name": "transfer learning", | 256 | "name": "transfer learning", | ||
257 | "state": "active", | 257 | "state": "active", | ||
258 | "vocabulary_id": null | 258 | "vocabulary_id": null | ||
259 | } | 259 | } | ||
260 | ], | 260 | ], | ||
261 | "third_party": "no", | 261 | "third_party": "no", | ||
262 | "title": "A Convolutional Neural Network with Image and Numerical | 262 | "title": "A Convolutional Neural Network with Image and Numerical | ||
263 | Data to Improve Farming of Edible Crickets as a Source of Food - A | 263 | Data to Improve Farming of Edible Crickets as a Source of Food - A | ||
264 | Decision Support System", | 264 | Decision Support System", | ||
265 | "type": "dataset", | 265 | "type": "dataset", | ||
266 | "url": null, | 266 | "url": null, | ||
267 | "version": null | 267 | "version": null | ||
268 | } | 268 | } |