Novel Quanvolutional Neural Network-Based COVID-19 Diagnosis From Raman Spectroscopic Signals of Human Serum by Shivanya Shomir Dutta, Sahil Sandeep, S. Sridevi, Rajiv Mistry, Jonathan Ortega, Gorkem Kar

“…COVID-19 has proven to be one of the most devastating pandemics of the 21st century, causing widespread mortality and overwhelming healthcare systems globally. …”
Get full text

Deep learning-based accurate detection of insects and damage in cruciferous crops using YOLOv5 by Sourav Chakrabarty, Pathour Rajendra Shashank, Chandan Kumar Deb, Md. Ashraful Haque, Pradyuman Thakur, Deeba Kamil, Sudeep Marwaha, Mukesh Kumar Dhillon

“…Therefore, to strike a balance between complexity and performance, YOLOv5l has emerged as the most viable option to integrate with AI-based insect identification applications. …”
Get full text

Pedestrian Crossing Direction Prediction at Intersections for Pedestrian Safety by Younggun Kim, Mohamed Abdel-Aty, Keechoo Choi, Zubayer Islam, Dongdong Wang, Shaoyan Zhai

“…Pedestrians are among the most vulnerable road users, with significant risks arising at intersections due to potential conflicts with vehicular traffic. …”
Get full text

Hybrid Wavelet-Attention Model for Detecting Changes in High-Resolution Remote Sensing Images by Lhuqita Fazry, MGS M. Luthfi Ramadhan, Alif Wicaksana Ramadhan, Muhammad Febrian Rachmadi, Aprinaldi Jasa Mantau, Lukito Edi Nugroho, Chi-Hung Chi, Wisnu Jatmiko

“…Change detection is one of the most difficult remote sensing tasks because the change to be detected (real-change) is mixed with apparent changes (pseudo-change) due to differences in the two images, such as brightness, humidity, seasonal differences, etc. …”
Get full text

MobilitApp: A Deep Learning-Based Tool for Transport Mode Detection to Support Sustainable Urban Mobility by Gerard Caravaca Ibanez, Luis J. de la Cruz Llopis, Adrian Catalin Diaconeasa, Alberto Bazan Guillen, Monica Aguilar Igartua

“…The model was trained on a dataset of multimodal trips in Barcelona, achieving over 80% accuracy for most transport modes and a weighted average accuracy of 88%. …”
Get full text

MFEM-CIN: A Lightweight Architecture Combining CNN and Transformer for the Classification of Pre-Cancerous Lesions of the Cervix by Peng Chen, Fobao Liu, Jun Zhang, Bing Wang

“…<italic>Goal:</italic> Cervical cancer is one of the most common cancers in women worldwide, ranking among the top four. …”
Get full text

STSA‐Based Early‐Stage Detection of Small Brain Tumors Using Neural Network by Nafiul Hasan, Md. Masud Rana, Md Mahmudul Hasan, AKM Azad, Dil Afroz, Md Mostafizur Rahman Komol, Mousumi Aktar, Mohammad Ali Moni

“…Among the input features, impedance (Z) was identified as the most significant contributor to classification accuracy, whereas the S‐parameter exhibited the lowest performance at 84.21% accuracy. …”
Get full text

Computerized Diagnosis Methods for Pediatric Cardiology: A Review by R. Shantha Selvakumari, Kumaradevan Punithakumar, D. Selvathi, S. Chrisilla, R. Sri Abinaya, Nilanjan Ray

“…Support Vector Machines with linear kernels are the most commonly used ML based classifiers in the reviewed papers. …”
Get full text

Segmentation-Guided Deep Learning for Glioma Survival Risk Prediction with Multimodal MRI by Jianhong Cheng, Hulin Kuang, Songhan Yang, Hailin Yue, Jin Liu, Jianxin Wang

“…Glioma survival risk prediction is of great significance for the individualized treatment and assessment programs. Currently, most deep learning based survival prediction paradigms rely on invasive and expensive histopathology and genomics methods. …”
Get full text

TomaFDNet: A multiscale focused diffusion-based model for tomato disease detection by Rijun Wang, Rijun Wang, Yesheng Chen, Fulong Liang, Xiangwei Mou, Xiangwei Mou, Guanghao Zhang, Hao Jin

“…IntroductionTomatoes are one of the most economically significant crops worldwide, with their yield and quality heavily impacted by foliar diseases. …”
Get full text

A ubiquitous and interoperable deep learning model for automatic detection of pleomorphic gastroesophageal lesions by Miguel Martins, Miguel José Mascarenhas, Maria João Almeida, João Afonso, Tiago Ribeiro, Pedro Cardoso, Francisco Mendes, Joana Mota, Patrícia Andrade, Hélder Cardoso, Miguel Mascarenhas-Saraiva, João Ferreira, Guilherme Macedo

“…Abstract In recent years, artificial intelligence (AI) has been widely explored to enhance capsule endoscopy (CE), with the goal of improving the efficiency of the reading process. While most AI models have been developed for small bowel and colon analysis, the development of esophagogastric (E-G) models has been limited due to the scarcity of frames captured during the procedure, making it challenging to develop a robust model. …”
Get full text

Next-generation cutting-edge hybrid AI frameworks for predicting rheological properties and CO₂ emissions in alkali-activated concrete by Lu Zhang, Kangning Liu, Ali H. AlAteah, Sadiq Alinsaif, Muhammad Sufian, Ayaz Ahmad

“…Furthermore, the models were extended to predict CO₂ emissions, with ANFIS-GA delivering the most accurate results, ranging between 22.51 and 68.27 kg/m³ , closely matching the experimental values. …”
Get full text

An Explainable Bayesian TimesNet for Probabilistic Groundwater Level Prediction by Zechen Peng, Shaoxing Mo, Alexander Y. Sun, Jichun Wu, Xiankui Zeng, Miao Lu, Xiaoqing Shi

“…SHAP analysis reveals that historical GWLs are the most informative features, with meteorological predictors making secondary contributions. …”
Get full text

Comparing efficiency of an attention-based deep learning network with contemporary radiological workflow for pulmonary embolism detection on CTPA: A retrospective study by Gagandeep Singh, Annie Singh, Tejasvi Kainth, Sudhir Suman, Nicole Sakla, Luke Partyka, Tej Phatak, Prateek Prasanna

“…Rational and objectives: Pulmonary embolism (PE) is the third most fatal cardiovascular disease in the United States. …”
Get full text

Investigation into the prognostic factors of early recurrence and progression in previously untreated diffuse large B-cell lymphoma and a statistical prediction model for POD12 by Ke Lian, Wenyao Zhu, Zhihui Hu, Fang Su, CaiXia Xu, Hui Wang

“…Comparatively, the CNN-LSTM and PSO-GRNN models are the most suitable to predict the risk level of the POD12 in the future.…”
Get full text

Multimodal Emotion Recognition Based on Facial Expressions, Speech, and EEG by Jiahui Pan, Weijie Fang, Zhihang Zhang, Bingzhi Chen, Zheng Zhang, Shuihua Wang

“…For work on the speech branch, this paper proposes a lightweight fully convolutional neural network (LFCNN) for the efficient extraction of speech emotion features. …”
Get full text

An exploratory analysis of longitudinal artificial intelligence for cognitive fatigue detection using neurophysiological based biosignal data by Sameer Nooh, Mahmoud Ragab, Rania Aboalela, Abdullah AL-Malaise AL-Ghamdi, Omar A. Abdulkader, Ghadah Alghamdi

“…The graph convolutional autoencoder (GCA) classifier is employed to classify cognitive fatigue detection. …”
Get full text

Frontotemporal dementia: a systematic review of artificial intelligence approaches in differential diagnosis by Serena Dattola, Augusto Ielo, Giuseppe Varone, Giuseppe Varone, Alberto Cacciola, Angelo Quartarone, Lilla Bonanno

“…Deep learning methods, particularly convolutional neural networks (CNNs), have also been increasingly adopted, demonstrating high accuracy in distinguishing FTD from other dementias. …”
Get full text

A multitask framework based on CA-EfficientNetV2 for the prediction of glioma molecular biomarkers by Qian Xu, Feng Ning Liang, Ya Ru Cao, Jin Duan, Teng Cui, Teng Zhao, Hong Zhu

“…IntroductionGlioma is the most common primary malignant tumor of the central nervous system. …”
Get full text

Internet of things driven object detection framework for consumer product monitoring using deep transfer learning and hippopotamus optimization by Amnah Alshahrani, Mukhtar Ghaleb, Hany Mahgoub, Achraf Ben Miled, Nojood O. Aljehane, Mohammed Yahya Alzahrani, Hasan Beyari, Sultan Alanazi

“…Object detection (OD) is the most significant and challenging problem in computer vision (CV). …”
Get full text