3D Capsule Networks for Object Classification With Weight Pruning
نویسندگان
چکیده
منابع مشابه
Investigating Capsule Networks with Dynamic Routing for Text Classification
In this study, we explore capsule networks with dynamic routing for text classification. We propose three strategies to stabilize the dynamic routing process to alleviate the disturbance of some noise capsules which may contain “background” information or have not been successfully trained. A series of experiments are conducted with capsule networks on six text classification benchmarks. Capsul...
متن کامل3D Object Recognition by Classification Using Neural Networks
In this Paper, a classification method based on neural networks is presented for recognition of 3D objects. Indeed, the objective of this paper is to classify an object query against objects in a database, which leads to recognition of the former. 3D objects of this database are transformations of other objects by one element of the overall transformation. The set of transformations considered ...
متن کاملUsing spinImages for 3D object classification
The subject of this thesis is to evaluate if a combination of spin images and Bag of Features classification can be used to categorize point clouds representing real world objects. At first, for each point cloud spin images are created as descriptors for the cloud’s points. Then vector quantization is used to learn prototypes in the spin image space. These prototypes are then used as a codebook...
متن کامل3D Scene and Object Classification Based on Information Complexity of Depth Data
In this paper the problem of 3D scene and object classification from depth data is addressed. In contrast to high-dimensional feature-based representation, the depth data is described in a low dimensional space. In order to remedy the curse of dimensionality problem, the depth data is described by a sparse model over a learned dictionary. Exploiting the algorithmic information theory, a new def...
متن کاملBrain Tumor Type Classification via Capsule Networks
Brain tumor is considered as one of the deadliest and most common form of cancer both in children and in adults. Consequently, determining the correct type of brain tumor in early stages is of significant importance to devise a precise treatment plan and predict patient’s response to the adopted treatment. In this regard, there has been a recent surge of interest in designing Convolutional Neur...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Access
سال: 2020
ISSN: 2169-3536
DOI: 10.1109/access.2020.2971950