In an embodiment, a computer-implemented method of detecting infected objects from large field-of-view images is disclosed. The method comprises receiving, by a processor, a digital image capturing multiple objects； generating, by the processor, a plurality of scaled images from the digital image respectfully corresponding to a plurality of scales； and computing a group of feature matrices for the digital image. The method further comprises, for each of the plurality of scaled images. selecting a list of candidate regions from the scaled image each likely to capture a single object； and for each of the list of candidate regions, performing the following steps: mapping the candidate region back to the digital image to obtain a mapped region； identifying a corresponding portion from each of the group of feature matrices based on the mapping； and determining whether the candidate region is likely to capture the single object infected with a disease based on the group of corresponding portions. In addition, the method comprises choosing a group of final regions from the lists of mapped regions based on the determining； and causing display of information regarding the group of final regions.
