… H represents the entire convolutional section of the CNN extracting the features from the
image of a camera. FC is the fully connected layer performing classification.(2) N E T s v = F C ∘ …

… techniques to automatically identify wildlife in camera trap imagery, which can … for object
detection in real field monitoring scenarios. In this study, we firstly constructed a wildlife image …

… camera captures and recognizes its surrounding based on a feature based image retrieval …
It allows our system to superimpose virtual visual effects to the omnidirectional camera image. …

… A camera sensor is one of the … (image signal processing), and a data transmission part. It
works by first collecting images using optical imaging principles and finally performing image …

… object detection using the IMU sensor and instance image segmentation. In the proposed
method, the feature points are extracted by the detector, … classification, image segmentation is …

… motion, it is necessary to consider object detection and recognition, especially for the robot
… -view 3D object detection networks combined with the Lidar point cloud and RGB image in …

… Inspired by the work in [21] that proposed an approach of vehicle type recognition using
training and test data obtained from different distributions and imaging procedure, we adopt this …

… of a physics-based camera model, various … image augmentation for the scope of training
a car detection DNN, and by using the KITTI dataset [4], we reveal its behavior on real camera …

… We examine the impact of different parameters that may affect image feature extraction and,
consequently, detection performance. Specifically, we experiment with various output sizes (…

… object detection system is used with a scanning high definition camera as its video image …
In this paper, we first use edge detection to get an edge difference image. After that, we …