Zobrazeno 1 - 10
of 97
pro vyhledávání: '"Maida, Anthony S."'
Since the onset of LLMs, translating natural language queries to structured SQL commands is assuming increasing. Unlike the previous reviews, this survey provides a comprehensive study of the evolution of LLM-based text-to-SQL systems, from early rul
Externí odkaz:
http://arxiv.org/abs/2410.01066
Autor:
Shahadat, Nazmul, Maida, Anthony S.
While convolutional neural networks (CNNs) demonstrate outstanding performance on computer vision tasks, their computational costs remain high. Several techniques are used to reduce these costs, like reducing channel count, and using separable and de
Externí odkaz:
http://arxiv.org/abs/2301.04631
Autor:
Shahadat, Nazmul, Maida, Anthony S.
Over the past decade, deep hypercomplex-inspired networks have enhanced feature extraction for image classification by enabling weight sharing across input channels. Recent works make it possible to improve representational capabilities by using hype
Externí odkaz:
http://arxiv.org/abs/2301.04626
Enhancing ResNet Image Classification Performance by using Parameterized Hypercomplex Multiplication
Autor:
Shahadat, Nazmul, Maida, Anthony S.
Recently, many deep networks have introduced hypercomplex and related calculations into their architectures. In regard to convolutional networks for classification, these enhancements have been applied to the convolution operations in the frontend to
Externí odkaz:
http://arxiv.org/abs/2301.04623
Long short-term memory (LSTM) is one of the robust recurrent neural network architectures for learning sequential data. However, it requires considerable computational power to learn and implement both software and hardware aspects. This paper propos
Externí odkaz:
http://arxiv.org/abs/2301.04794
Hearing-impaired is the disability of partial or total hearing loss that causes a significant problem for communication with other people in society. American Sign Language (ASL) is one of the sign languages that most commonly used language used by H
Externí odkaz:
http://arxiv.org/abs/2204.04235
Long short-term memory (LSTM) is a robust recurrent neural network architecture for learning spatiotemporal sequential data. However, it requires significant computational power for learning and implementing from both software and hardware aspects. T
Externí odkaz:
http://arxiv.org/abs/2201.11624
Autor:
Shahadat, Nazmul, Maida, Anthony S.
In recent years, hypercomplex-inspired neural networks (HCNNs) have been used to improve deep learning architectures due to their ability to enable channel-based weight sharing, treat colors as a single entity, and improve representational coherence
Externí odkaz:
http://arxiv.org/abs/2110.01185
Blood glucose (BG) management is crucial for type-1 diabetes patients resulting in the necessity of reliable artificial pancreas or insulin infusion systems. In recent years, deep learning techniques have been utilized for a more accurate BG level pr
Externí odkaz:
http://arxiv.org/abs/2101.06850
Autor:
Shahadat, Nazmul, Maida, Anthony S.
Publikováno v:
In Image and Vision Computing January 2024 141
