Convolutional neural network vs bag of features for bambara groundnut leaf disease recognition
نویسندگان
چکیده
منابع مشابه
EMG-based wrist gesture recognition using a convolutional neural network
Background: Deep learning has revolutionized artificial intelligence and has transformed many fields. It allows processing high-dimensional data (such as signals or images) without the need for feature engineering. The aim of this research is to develop a deep learning-based system to decode motor intent from electromyogram (EMG) signals. Methods: A myoelectric system based on convolutional ne...
متن کاملLearning Document Image Features With SqueezeNet Convolutional Neural Network
The classification of various document images is considered an important step towards building a modern digital library or office automation system. Convolutional Neural Network (CNN) classifiers trained with backpropagation are considered to be the current state of the art model for this task. However, there are two major drawbacks for these classifiers: the huge computational power demand for...
متن کاملOn the use of Textural Features and Neural Networks for Leaf Recognition
for recognizing various types of plants, so automatic image recognition algorithms can extract to classify plant species and apply these features. Fast and accurate recognition of plants can have a significant impact on biodiversity management and increasing the effectiveness of the studies in this regard. These automatic methods have involved the development of recognition techniques and digi...
متن کاملConvolutional Neural Network for Humor Recognition
For the purpose of automatically evaluating speakers’ humor usage, we build a presentation corpus containing humorous utterances based on TED talks. Compared to previous data resources supporting humor recognition research, ours has several advantages, including (a) both positive and negative instances coming from a homogeneous data set, (b) containing a large number of speakers, and (c) being ...
متن کامل3D Convolutional Neural Network for Object Recognition
3D Object recognition is an important task in computer vision applications. After the success of convolutional neural networks for object recognition in 2D images, many researchers have designed convolution neural network (CNN) for 3D object recognition. The state of art methods provide favourable results. However, the availability of large/dynamic 3D dataset and computational complexity of CNN...
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: Indonesian Journal of Electrical Engineering and Computer Science
سال: 2019
ISSN: 2502-4760,2502-4752
DOI: 10.11591/ijeecs.v14.i1.pp368-374