Spatial Prediction of Soil Continuous and Categorical Properties Using Deep Learning Approaches for Tamil Nadu, India by Thamizh Vendan Tarun Kshatriya, Ramalingam Kumaraperumal, Sellaperumal Pazhanivelan, Nivas Raj Moorthi, Dhanaraju Muthumanickam, Kaliaperumal Ragunath, Jagadeeswaran Ramasamy

“…The validation and test results obtained for each of the soil attributes for both the algorithms were most comparable with the DL-MLP algorithm depicting the attributes’ most intricate spatial organization details, compared to the 1D-CNN model. …”
Get full text

Comparison of Faster R-CNN and YOLOv5 for Overlapping Objects Recognition by Muhamad Munawar Yusro, Rozniza Ali, Muhammad Suzuri Hitam

Get full text

A Deep Learning-Driven CAD for Breast Cancer Detection via Thermograms: A Compact Multi-Architecture Feature Strategy by Omneya Attallah

“…Breast cancer continues to be the most common malignancy among women worldwide, presenting a considerable public health issue. …”
Get full text

Synergistic use of SAR satellites with deep learning model interpolation for investigating of active landslides in Cuenca, Ecuador by Mohammad Amin Khalili, Silvio Coda, Domenico Calcaterra, Diego Di Martire

“…Among the most intense geological disasters, landslides frequently occur throughout the world. …”
Get full text

Evaluation of Similarity of Image Explanations Produced by SHAP, LIME and Grad-CAM by Vladyslav Yavtukhovskyi, Violeta Tretynyk

“…Introduction. Convolutional neural networks (CNNs) are a subtype of neural networks developed specifically to work with images [1]. …”
Get full text

Comprehensive Evaluation of Techniques for Intelligent Chatter Detection in Micro-Milling Processes by Guilherme Serpa Sestito, Wesley Angelino De Souza, Alessandro Roger Rodrigues, Maira Martins Da Silva

“…Frictional and regenerative chatter are the most relevant unstable dynamic conditions in micro-milling. …”
Get full text

Image-Based Malicious Network Traffic Detection Framework: Data-Centric Approach by Doo-Seop Choi, Taeguen Kim, Boojoong Kang, Eul Gyu Im

“…Artificial intelligence (AI) algorithms have been widely used to detect malicious traffic, but most previous work focused on improving accuracy with various AI algorithms. …”
Get full text

Consistency regularization based semi-supervised plant disease recognition by Murat Ilsever, Ipek Baz

Get full text

Interpretation and understanding of asphalt crack detection deep learning models using integrated gradient (I.G.) maps by Gihan P. Ruwanpathirana, Sadeep Thilakarathna, Shanaka Kristombu Baduge

“…However, this approach is labour-intensive and time-consuming, prompting most authorities to transition to automated crack identification methods utilising Artificial Intelligence (A.I.). …”
Get full text

Detection of Cardiovascular Diseases Using Predictive Models Based on Deep Learning Techniques: A Hybrid Neutrosophic AHP-TOPSIS Approach for Model Selection by Julio Barzola-Monteses, Rosangela Caicedo-Quiroz, Franklin Parrales-Bravo, Cristhian Medina-Suarez, Wendy Yanez-Pazmino, David Zabala-Blanco, Maikel Y. Leyva-Vazquez

“…In this work, three different models were proposed and compared: deep neural networks (DNN), convolutional neural networks (CNN), and multilayer perceptron (MLP). …”
Get full text

Interpreting CNN models for musical instrument recognition using multi-spectrogram heatmap analysis: a preliminary study by Rujia Chen, Akbar Ghobakhlou, Ajit Narayanan

“…MFCC and Log-Mel spectrograms demonstrated superior performance across most instruments, while others provided insights into specific characteristics.DiscussionThis analysis provides some insights into optimizing spectrogram-based approaches for musical instrument recognition, offering guidance for future model development and improving interpretability through statistical and visual analyses.…”
Get full text

New Strategies Based on Hierarchical Matrices for Matrix Polynomial Evaluation in Exascale Computing Era by Luisa Carracciuolo, Valeria Mele

“…Historically, improvements in computing platforms were mostly dependent on simultaneous developments in hardware, software, architecture, and algorithms (a process known as co-design), which raised the performance of computational models. …”
Get full text

Intelligent Recognition Method for Ferrography Wear Debris Images Using Improved Mask R-CNN Methods by Xiangwen Xiao, Weixuan Zhang, Qing Wang, Yuan Liu, Yishou Wang

“…The improvement on the Mask R-CNN focuses on two key aspects: enhancing feature extraction through the feature pyramid network structure and integrating attention mechanisms. The most suitable attention mechanism for wear debris detection was determined through ablation experiments. …”
Get full text

Image captioning deep learning model using ResNet50 encoder and hybrid LSTM–GRU decoder optimized with beam search by P. V. Kavitha, V. Karpagam

Get full text

Dynamic Range Expansion Using Cumulative Histogram Learning for High Dynamic Range Image Generation by Hanbyol Jang, Kihun Bang, Jinseong Jang, Dosik Hwang

Get full text

The Improved Kurdish Dialect Classification Using Data Augmentation and ANOVA-Based Feature Selection by Karzan J. Ghafoor, Sarkhel H. Karim, Karwan M. Hama Rawf, Ayub O. Abdulrahman

“…Analysis of variance (ANOVA) filter approach is applied to improve feature selection (FS) more efficiently and highlight the most relevant features for dialect classification. …”
Get full text

Alternate encoder and dual decoder CNN-Transformer networks for medical image segmentation by Lin Zhang, Xinyu Guo, Hongkun Sun, Weigang Wang, Liwei Yao

“…In recent years, methods based on convolutional neural networks and Transformer have achieved great success in the medical image segmentation field. …”
Get full text

Deep learning techniques for speech emotion recognition: A review by Silviana Widya Lestari, Saliyah Kahar, Trismayanti Dwi

Get full text

A Lightweight Breast Cancer Mass Classification Model Utilizing Simplified Swarm Optimization and Knowledge Distillation by Wei-Chang Yeh, Wei-Chung Shia, Yun-Ting Hsu, Chun-Hui Huang, Yong-Shiuan Lee

Get full text

Assessing the allergenic potential of urban green spaces using orthoimagery and airborne LiDAR data by Jinzhou Wu, Robbe Neyns, Markus Münzinger, Frank Canters

“…Over the past decades, pollen allergy has become one of the most widespread public health issues. The number of individuals having allergies to pollen has dramatically increased, especially in urban and industrial areas. …”
Get full text