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pro vyhledávání: '"Kota, Akshith"'
Causal networks are widely used in many fields to model the complex relationships between variables. A recent approach has sought to construct causal networks by leveraging the wisdom of crowds through the collective participation of humans. While th
Externí odkaz:
http://arxiv.org/abs/2410.14146
Autor:
Zhang, Yanming, Fitzgibbon, Brette, Garofolo, Dino, Kota, Akshith, Papenhausen, Eric, Mueller, Klaus
Causal networks are widely used in many fields, including epidemiology, social science, medicine, and engineering, to model the complex relationships between variables. While it can be convenient to algorithmically infer these models directly from ob
Externí odkaz:
http://arxiv.org/abs/2312.16211
Autor:
Gangapatnam Sai Ananya, Kota Akshith Reddy, Teja Naveen Chintapalli, Jahnavi Polsani, Satish C J
Publikováno v:
International Journal of Recent Technology and Engineering (IJRTE). 10:131-139
Automatic Image Caption Generation is one of the core problems in the field of Deep Learning. Data Augmentation is a technique which helps in increasing the amount of data at hand and this is done by augmenting the training data using various techniq
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9c24c1f61e1fcdafcfe54e701f974519
https://doi.org/10.35940/ijrte.c6439.0910321
https://doi.org/10.35940/ijrte.c6439.0910321
Autor:
Kota Akshith Reddy, Sharmila Banu K, Pursuing, B.Tech , India., Jahnavi Polsani, Chandra Havish Siddareddi, Sai Kanishka Ippagunta
Publikováno v:
International Journal of Engineering and Advanced Technology. 10:79-91
The apple is one of the most cultivated fruits in the world. They are round in shape and their color varies from green to red. Apple Orchards face constant threats from a large number of insects and pathogens and the early detection of these diseases
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4198fcd2b40446f333ac68ce6e1690fa
https://doi.org/10.35940/ijeat.f3040.0810621
https://doi.org/10.35940/ijeat.f3040.0810621