as the information carried in a high spatial resolution image is not represented by single pixels but by meaningful image objects, which include the association of multiple pixels and their mutual relations, the object based method has become one of the most commonly used strategies for the processing of high resolution imagery. this processing comprises two fundamental and critical steps towar...

The training of deep learning models generally requires a large amount annotated data for effective convergence and generalisation. However, obtaining high-quality annotations is laboursome expensive process due to the need expert radiologists labelling task. study semi-supervised in medical image analysis then crucial importance given that it much less obtain unlabelled images than acquire lab...

employing recent technological advances in surveying and mapping soil salinity is a step forward in controlling saline soils. the aim of this study was to map the topsoil salinity, the depth of 0-5 cm, using different methods within the environmental context of the area around tashk & bakhtegan lake, with the area of 8062 ha, that in this region soil salinity appears to be a major threat to agr...

Due to the scarcity and high cost of labeled hyperspectral image (HSI) samples, many deep learning methods driven by massive data cannot achieve intended expectations. Semi-supervised self-supervised algorithms have advantages in coping with this phenomenon. This paper primarily concentrates on applying strategies make strides semi-supervised HSI classification. Notably, we design an effective ...

The maximum entropy principle advocates to evaluate events’ probabilities using a distribution that maximizes among those satisfy certain expectations’ constraints. Such can be generalized for arbitrary decision problems where it corresponds minimax approaches. This paper establishes framework supervised classification based on the leads risk classifiers (MRCs). We develop learning techniques d...

Semi-supervised classification methods make use of the large amounts of relatively inexpensive available unlabeled data along with the small amount of labeled data to improve the accuracy of the classification. This article presents a novel ‘self-training’ based semi-supervised classification algorithm using the property of aggregation pheromone found in natural behavior of real ants. The propo...