Results 91 to 100 of about 176,660 (282)

DeepMapper: Attention‐Based AutoEncoder for System Identification in Wound Healing and Stage Prediction

Advanced Intelligent Discovery, EarlyView.
The authors develop a deep learning model for real‐time tracking of wound progression. The deep learning framework maps the nonlinear evolution of a time series of images to a latent space, where they learn a linear representation of the dynamics. The linear model is interpretable and suitable for applications in feedback control.
Fan Lu, Ksenia Zlobina, Michael Briden, Oscar Avalos, Héctor Carrión, Sebastian Osorio, Hsin‐ya Yang, Alexandra Nava, Michelle D. Bagood, Marco Rolandi, Roslyn Rivkah Isseroff, Marcella Gomez   +11 more
wiley   +1 more source

PREDICTING MEDICINE DEMAND USING DEEP LEARNING TECHNIQUES

Iraqi Journal for Computers and Informatics, 2023
Medication supply and storage are essential components of the medical industry and distribution. Most medications have a predetermined expiration date. When the demand is met in large quantities that exceed the actual need, this leads to the accumulation
Bashaer Abdurahman Mousa, Belal Al-Khateeb   +1 more
doaj  

When Biology Meets Medicine: A Perspective on Foundation Models

Advanced Intelligent Discovery, EarlyView.
Artificial intelligence, and foundation models in particular, are transforming life sciences and medicine. This perspective reviews biological and medical foundation models across scales, highlighting key challenges in data availability, model evaluation, and architectural design.
Kunying Niu, Yuxing Wang, Limin Zou, Jing Huang   +3 more
wiley   +1 more source

Amélioration de la gestion des centrales d'énergie nucléaire par l'introduction de l'intelligence artificielle et synthétique

Revue des Sciences de la Santé
L'énergie nucléaire est une source de production d'énergie à haut rendement, mais sa gestion présente des défis techniques et sécuritaires majeurs. Le Centre de Recherche en Énergie Nucléaire de l'Université de Kinshasa (C.RE.N.K - UNIKIN) se trouve à la
Vincent KASUENDE NTAMBWE NGANDU, Leonard WOTO MAKONTSHI, Justin KHUALA MVUMBI   +2 more
doaj   +1 more source

Recurrent Neural Networks For Accurate RSSI Indoor Localization

, 2019
This paper proposes recurrent neuron networks (RNNs) for a fingerprinting indoor localization using WiFi. Instead of locating user's position one at a time as in the cases of conventional algorithms, our RNN solution aims at trajectory positioning and ...
Dong, Xiaodai, Hoang, Minh Tu, Lu, Tao, Reddy, Kishore, Westendorp, Robert, Yuen, Brosnan   +5 more
core  

VAE+DDPG: An Attention‐Enhanced Variational Autoencoder for Deep Reinforcement Learning‐Based Autonomous Navigation in Low‐Light Environments

Advanced Intelligent Systems, EarlyView.
Variational Autoencoder+Deep Deterministic Policy Gradient addresses low‐light failures of infrared depth sensing for indoor robot navigation. Stage 1 pretrains an attention‐enhanced Variational Autoencoder (Convolutional Block Attention Module+Feature Pyramid Network) to map dark depth frames to a well‐lit reconstruction, yielding a 128‐D latent code ...
Uiseok Lee, Chanhong Hwang, Hyunseok Kang, Yechan Park, Hangwoo Jin, Tuan Anh Nguyen, Eunmi Choi, Dugki Min   +7 more
wiley   +1 more source

Device‐Level Implementation of Reservoir Computing With Memristors

Advanced Intelligent Systems, EarlyView.
Reservoir computing (RC) is an emerging computing scheme that employs a reservoir and a single readout layer, which can be actualized in the nanoscale with memristors. As a comprehensive overview, the principles of RC and the switching mechanisms of memristors are discussed, followed by actual demonstrations of memristor‐based RC and the remaining ...
Sunbeom Park, Hyojung Kim, Ho Won Jang
wiley   +1 more source

Integrating Artificial Intelligence With Droplet‐Based Microfluidics: Advances, Challenges, and Emerging Opportunities

Advanced Intelligent Systems, EarlyView.
Droplet‐based microfluidics enables precise, high‐throughput microscale reactions but continues to face challenges in scalability, reproducibility, and data complexity. This review examines how artificial intelligence enhances droplet generation, detection, sorting, and adaptive control and discusses emerging opportunities for clinical and industrial ...
Junyan Lai, Sukrit Gaira, Rongfeng Wang, Qingtian Zhang, Ming Li, Liao Wu, Diangeng Li, Yi Li, Chengchen Zhang, Jinhong Guo, Shi‐Yang Tang   +10 more
wiley   +1 more source

Channel and model selection for multi-channel EEG input to neural networks

SICE Journal of Control, Measurement, and System Integration
Studies employing neural networks to classify emotions from brain waves and other biological signals provide a quantitative perspective on understanding human physiological phenomena.
Kento Harachi, Yusuke Yamamoto, Ayumi Muramatsu, Hajime Nagahara, Noriko Takemura, Shinji Shimojo, Daisuke Furihata, Yuko Mizuno-Matsumoto   +7 more
doaj   +1 more source

دراسة إحصائية مقارنة للتنبؤ بإيرادات الموارد النفطية في جمهورية مصر العربية باستخدام نماذج الشبكات العصبية المتكررة [PDF]

Maǧallaẗ Al-Buḥūṯ Al-Mālīyyaẗ wa Al-Tiğāriyyaẗ
ملخص البحثيهدف هذا البحث إلى مقارنة كفاءة ودقة التنبؤ بإيرادات الموارد النفطية (ORR) باستخدام نماذج الشبكات العصبية المتكررة (RNN) مثل LSTM وGRU، بالإضافة إلى نماذج السلاسل الزمنية متعددة المتغيرات.
AHMED MOHAMED MOHEY ELDEEN AL HOSAFY
doaj   +1 more source