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Novel deep learning-based computer-aided diagnosis system for predicting inflammatory activity in ulcerative colitis.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: Endoscopy is increasingly performed for evaluating patients with ulcerative colitis (UC). However, its diagnostic accuracy is largely affected by the subjectivity of endoscopists' experience and scoring methods, and scoring of se...

Design of Convolutional Neural Network Processor Based on FPGA Resource Multiplexing Architecture.

Sensors (Basel, Switzerland)
As CNNs are widely used in fields such as image classification and target detection, the total number of parameters and computation of the models is gradually increasing. In addition, the requirements on hardware resources and power consumption for d...

Computer-Aided Multiclass Classification of Corn from Corn Images Integrating Deep Feature Extraction.

Computational intelligence and neuroscience
Corn has great importance in terms of production in the field of agriculture and animal feed. Obtaining pure corn seeds in corn production is quite significant for seed quality. For this reason, the distinction of corn seeds that have numerous variet...

Computer-aided anatomy recognition in intrathoracic and -abdominal surgery: a systematic review.

Surgical endoscopy
BACKGROUND: Minimally invasive surgery is complex and associated with substantial learning curves. Computer-aided anatomy recognition, such as artificial intelligence-based algorithms, may improve anatomical orientation, prevent tissue injury, and im...

Intelligent User Interfaces and Their Evaluation: A Systematic Mapping Study.

Sensors (Basel, Switzerland)
Intelligent user interfaces (IUI) are driven by the goal of improvement in human-computer interaction (HCI), mainly improving user interfaces' user experience (UX) or usability with the help of artificial intelligence. The main goal of this study is ...

Coupled Attention Framework of Convolutional Neural Network Based on Computer Intelligence.

Computational intelligence and neuroscience
Using an attention mechanism based on the convolutional neural networks (CNNs) improves the performance of computer vision tasks by enhancing the representation of the features. The existing attention methods enhance the expression of the features by...

Toward Full-Stack Acceleration of Deep Convolutional Neural Networks on FPGAs.

IEEE transactions on neural networks and learning systems
Due to the huge success and rapid development of convolutional neural networks (CNNs), there is a growing demand for hardware accelerators that accommodate a variety of CNNs to improve their inference latency and energy efficiency, in order to enable...

Secure deep learning for distributed data against malicious central server.

PloS one
In this paper, we propose a secure system for performing deep learning with distributed trainers connected to a central parameter server. Our system has the following two distinct features: (1) the distributed trainers can detect malicious activities...

Research on Blended Teaching of Flipped Classroom Based on CNN-SSA-Bi-LSTM Deep Learning Model Computer Media.

Computational intelligence and neuroscience
Aiming at the problem that the influencing factors of computer media flipped classroom hybrid teaching lead to the teaching effect not reaching the expected, this study proposes an ultra-short-term prediction model based on CNN-SSA-Bi-LSTM. CNN-SSA-B...

Computer-aided extraction of select MRI markers of cerebral small vessel disease: A systematic review.

NeuroImage
Cerebral small vessel disease (CSVD) is a major vascular contributor to cognitive impairment in ageing, including dementias. Imaging remains the most promising method for in vivo studies of CSVD. To replace the subjective and laborious visual rating ...