Colorectal polyp region extraction using saliency detection network with neutrosophic enhancement
Colorectal polyp recognition is crucial for early colorectal cancer detection and treatment.
Colonoscopy is always employed for colorectal polyp scanning. However, one out of four …
Colonoscopy is always employed for colorectal polyp scanning. However, one out of four …
A fuzzy convolutional neural network for enhancing multi-focus image fusion
The images captured by the cameras contain distortions, misclassified pixels, uncertainties
and poor contrast. Therefore, the multi-focus image fusion (MFIF) integrates various input …
and poor contrast. Therefore, the multi-focus image fusion (MFIF) integrates various input …
Implementation and Analysis of AI‐Based Gesticulation Control for Impaired People
S Nivash, EN Ganesh, T Manikandan… - Wireless …, 2022 - Wiley Online Library
This paper presents an intelligent human PC intuitive framework. In this proposed work,
artificial intelligence is utilized for home mechanization, which perceives human motions …
artificial intelligence is utilized for home mechanization, which perceives human motions …
[PDF][PDF] Fusion of Infrared and Visible Images Using Fuzzy Based Siamese Convolutional Network.
Traditional techniques based on image fusion are arduous in integrating complementary or
heterogeneous infrared (IR)/visible (VS) images. Dissimilarities in various kind of features in …
heterogeneous infrared (IR)/visible (VS) images. Dissimilarities in various kind of features in …
Transformer based conditional GAN for multimodal image fusion
Multimodal Image fusion is becoming urgent in multi-sensor information utilization. However,
existing end-to-end image fusion frameworks ignore a priori knowledge integration and long …
existing end-to-end image fusion frameworks ignore a priori knowledge integration and long …
Combining transformers with CNN for multi-focus image fusion
Z Duan, X Luo, T Zhang - Expert Systems with Applications, 2024 - Elsevier
Recently, deep convolutional neural network (CNN) based methods for multi-focus image
fusion have achieved adequate performance. However, most of them cannot obtain spatially …
fusion have achieved adequate performance. However, most of them cannot obtain spatially …
Forecasting COVID‐19 Pandemic Using Prophet, ARIMA, and Hybrid Stacked LSTM‐GRU Models in India
Due to the proliferation of COVID‐19, the world is in a terrible condition and human life is at
risk. The SARS‐CoV‐2 virus had a significant impact on public health, social issues, and …
risk. The SARS‐CoV‐2 virus had a significant impact on public health, social issues, and …
Cyberbullying detection using deep transfer learning
PK Roy, FU Mali - Complex & Intelligent Systems, 2022 - Springer
Social networking platforms like Facebook, Twitter, and others have numerous advantages,
but they have many dark sides also. One of the issues on these social platforms is …
but they have many dark sides also. One of the issues on these social platforms is …
Medical image fusion based on sparse representation and neighbor energy activity
X Li, W Wan, F Zhou, X Cheng, Y Jie, H Tan - Biomedical Signal Processing …, 2023 - Elsevier
Medical image fusion has become popular in recent years. The fused image can provide a
more objective and comprehensive description of lesions and has significant clinical …
more objective and comprehensive description of lesions and has significant clinical …
AEFusion: A multi-scale fusion network combining Axial attention and Entropy feature Aggregation for infrared and visible images
B Li, J Lu, Z Liu, Z Shao, C Li, Y Du, J Huang - Applied Soft Computing, 2023 - Elsevier
The purpose of image fusion is to generate an image that contains more complementary
information. Existing image fusion methods suffer from loss of detail information, artifacts …
information. Existing image fusion methods suffer from loss of detail information, artifacts …