Leaf Classification: An application of deep reinforcement learning This model trains on grayscale images of 99 different species of leaves. Approximately 1580+ images in all and 16 images per species. For full description of the dataset see kaggle. Requirements: python 3.5 tensorflow keras theano in...
The dataset contains a total of 1720 original images, that can be utilized to train DL models to detect groundnut leaf diseases at an early stage. Additionally, we provide baseline results of applying state-of-the-art CNN architectures on the dataset for groundnut disease classification, ...
Two challenging qualities in an image classification dataset are the similarity among elements from different classes (inter-class correlation) and the diversity inside each class (intra-class coefficient). Like any real-world dataset, the Peruvian Amazon Forestry Dataset registers a high inter-class ...
In this post, I am going to run an exploratory analysis of the plant leaf dataset as made available by UCI Machine Learning repository atthis link. The dataset is expected to comprise sixteen samples each of one-hundred plant species. Its analysis was introduced within ref. [1]. That paper...
and margin. The dataset used for this experiment is the Swedish leaf dataset, a database of 15 different plant species with 1125 leaf images. Experimental results showed that random forest (RF) achieved a classification accuracy of 98.83% against other ML algorithms with a combination of grayscal...
Proposed model block diagram of classification Full size image The starting point of the workflow is SLD input images which are first resized in order to be suitable for the processing step. The partition prepares the dataset into three subsections: training, validation, and testing. To increase ...
“Material and methods” focuses on materials and methods, detailing the dataset employed for testing the efficiency of the presented model in classification. “Experimental results and discussion” presents experimental results and discussion, highlighting the advantages of the proposed model, providing a...
Thus, if we split the dataset here, the resulting four sample partition will be 100% pure for Play=yes. Mathematically for this partition, the entropy can be calculated using Eq. (4.1) as: Sign in to download full-size image Figure 4.2. Splitting the data on the Outlook attribute. H...
The classification was performed by requiring 30 classes with a regularization parameter T value of 2 and 30 iterations. The circular mask used for classification was set at 1,300 Å. The in-plane angular sampling was 2 and a wide offset search of 15 pixels was used with an offset ...
Download: Download high-res image (145KB) Download: Download full-size image Fig. 3. Implicit Head of YOLOv7-T. 2.2.2. YOLOv7-T loss function The YOLOv7-T algorithm’s loss function, similar to YOLOv5 (Jocher, 2020), consists of three main components: classification loss (Lcls), bo...