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An Improved Deep Residual Convolutional Neural Network for Plant Leaf Disease Detection.

Computational intelligence and neuroscience
In this research, we proposed a novel deep residual convolutional neural network with 197 layers (ResNet197) for the detection of various plant leaf diseases. Six blocks of layers were used to develop ResNet197. ResNet197 was trained and tested using...

Industrial equipment detection algorithm under complex working conditions based on ROMS R-CNN.

PloS one
In the paper, we proposed a deep learning-based industrial equipment detection algorithm ROMS R-CNN (Rotation Occlusion Multi-Scale Region-CNN). It can solve the problem of inaccurate detection of industrial equipment under complex working conditions...

Screening of factors influencing catheter rotation of a vascular interventional surgical robot using design of experiment approach.

Medical engineering & physics
Over the past decades, Vascular Interventional Surgery Robots (VISR) have been developed to address the risks associated with X-rays used in minimally invasive vascular surgery procedures. Manipulation of over-the-wire catheters is necessary to perfo...

Feature-based intelligent models for optimisation of percussive drilling.

Neural networks : the official journal of the International Neural Network Society
As a rotary-percussion system, the vibro-impact drilling (VID) system utilises resonantly induced high frequency periodic impacts alongside existing drill-string rotation to cut through downhole rock layers. Due to the inhomogeneous nature of the roc...

Learning online visual invariances for novel objects via supervised and self-supervised training.

Neural networks : the official journal of the International Neural Network Society
Humans can identify objects following various spatial transformations such as scale and viewpoint. This extends to novel objects, after a single presentation at a single pose, sometimes referred to as online invariance. CNNs have been proposed as a c...

IMU Motion Capture Method with Adaptive Tremor Attenuation in Teleoperation Robot System.

Sensors (Basel, Switzerland)
Teleoperation robot systems can help humans perform tasks in unstructured environments. However, non-intuitive control interfaces using only a keyboard or joystick and physiological tremor reduce the performance of teleoperation. This paper presents ...

Oblique and rotation double random forest.

Neural networks : the official journal of the International Neural Network Society
Random Forest is an ensemble of decision trees based on the bagging and random subspace concepts. As suggested by Breiman, the strength of unstable learners and the diversity among them are the ensemble models' core strength. In this paper, we propos...

Comparison of Transfer Learning Models in Pelvic Tilt and Rotation Measurement in Pediatric Anteroposterior Pelvic Radiographs.

Journal of digital imaging
The rotation and tilt of the pelvis during anteroposterior pelvic radiography can lead to misdiagnosis of developmental dysplasia of the hip (DDH) in children. At present, no method exists for accurately and conveniently measuring the precise rotatio...

Interactive and synergistic behaviours of multiple heterogeneous microrobots.

Lab on a chip
Microrobots have been extensively studied for biomedical applications, and significant innovations and advances have been made in diverse aspects of the field. However, most studies have been based on individual microrobots with limited capabilities,...

Technical note: A method to synthesize magnetic resonance images in different patient rotation angles with deep learning for gantry-free radiotherapy.

Medical physics
BACKGROUND: Recently, patient rotating devices for gantry-free radiotherapy, a new approach to implement external beam radiotherapy, have been introduced. When a patient is rotated in the horizontal position, gravity causes anatomic deformation. For ...