|
|
|
|
|
Catur Supriyanto, Abu Salam, Junta Zeniarja and Adi Wijaya
This research paper presents a deep-learning approach to early detection of skin cancer using image augmentation techniques. We introduce a two-stage image augmentation process utilizing geometric augmentation and a generative adversarial network (GAN) t...
ver más
|
|
|
|
|
|
|
|
|
Wenxin Yang, Xiaoli Zhi and Weiqin Tong
Current edge devices for neural networks such as FPGA, CPLD, and ASIC can support low bit-width computing to improve the execution latency and energy efficiency, but traditional linear quantization can only maintain the inference accuracy of neural netwo...
ver más
|
|
|
|
|
|
|
|
|
Sundas Iftikhar, Muhammad Asim, Zuping Zhang, Ammar Muthanna, Junhong Chen, Mohammed El-Affendi, Ahmed Sedik and Ahmed A. Abd El-Latif
In smart cities, target detection is one of the major issues in order to avoid traffic congestion. It is also one of the key topics for military, traffic, civilian, sports, and numerous other applications. In daily life, target detection is one of the ch...
ver más
|
|
|
|
|
|
|
|
|
Hao Wang and Nanfeng Xiao
In order to better utilize and protect marine organisms, reliable underwater object detection methods need to be developed. Due to various influencing factors from complex and changeable underwater environments, the underwater object detection is full of...
ver más
|
|
|
|
|
|
|
|
|
Gauri Vaidya, Meghana Kshirsagar and Conor Ryan
Neural networks have revolutionised the way we approach problem solving across multiple domains; however, their effective design and efficient use of computational resources is still a challenging task. One of the most important factors influencing this ...
ver más
|
|
|
|